I am a final year PhD student in the Department of Electrical Engineering and Computer Science (EECS) at Massachusetts Institute of Technology (MIT), advised by Prof. Cathy Wu. Prior to MIT, I received my bachelor’s and master’s degrees in EECS from UC Berkeley in 2017 and 2018, respectively. My research interest broadly lies in the intersection between machine learning and large-scale multi-agent systems relating to transportation, logistics, and robotics. Besides research, I’m also an avid engineer with numerous software projects across many different programming languages. I’ve spent time at DeepMind, Amazon Robotics, and several other companies as an intern.

Articles and Publications (First-Author)

Please see Google Scholar for the full list of all publications.

Neural Neighborhood Search for Multi-agent Path Finding [MIT News] [OpenReview]
Zhongxia Yan, Cathy Wu
ICLR, 2024.
Multi-agent Path Finding for Cooperative Autonomous Driving [arXiv] [GitHub]
Zhongxia Yan, Han Zheng, Cathy Wu
ICRA, 2024
Unified Automatic Control of Vehicular Systems with Reinforcement Learning [Blog] [arXiv] [IEEE] [GitHub]
Zhongxia Yan, Abdul R. Kreidieh, Eugene Vinitsky, Alexandre Bayen, Cathy Wu
IEEE T-ASE, 2022; IROS, 2022
Learning to Delegate for Large-scale Vehicle Routing [MIT News] [Blog] [arXiv] [Poster] [GitHub]
Sirui Li*, Zhongxia Yan*, Cathy Wu
NeurIPS, 2021; Spotlight, top 3%
* equal contribution
Reinforcement Learning for Mixed-Autonomy Intersections [arXiv] [IEEE] [GitHub]
Zhongxia Yan, Cathy Wu
IEEE ITSC, 2021
MicroNet for Efficient Language Modeling [arXiv] [PMLR] [Talk] [GitHub]
Zhongxia Yan, Hanrui Wang, Demi Guo, Song Han
NeurIPS 2019 MicroNet Competition 1st Place; PMLR, 2020
Meta‐analysis of massively parallel reporter assays enables prediction of regulatory function across cell types [Paper]
Anat Kreimer*, Zhongxia Yan*, Nadav Ahituv, Nir Yosef
Human Mutation, 2019
* equal contribution

Under Review

Transferability of Reinforcement Learning in Large and Parameterized Mixed Autonomy Systems
Zhongxia Yan, Cathy Wu
Under review at IEEE T-ITS

Teaching

I’ve been a teaching assistant for several courses at MIT and Berkeley:
6.883 Meta-Learning (MIT, Fall 2020)
6.246 Reinforcement Learning (MIT, Spring 2020)
6.867 Machine Learning (MIT, Fall 2019)
CS176 Algorithms for Computation Biology (Berkeley, Fall 2017)

Awards

2020 Frederick C. Hennie III Teaching Award, MIT EECS
2020 David Dwight Eisenhower Transportation Fellowship Program (DDETFP) Fellow
2014 USA Biology Olympiad Bronze Medalist (top 12 in USA)